Haplotype Inference on Pedigrees with Recombinations and Mutations

Abstract. Haplotype Inference (HI) is a computational challenge of crucial importance in a range of genetic studies, such as functional genomics, pharmacogenetics and population genetics. Pedigrees have been shown a valuable data that allows us to infer haplotypes from genotypes more accurately than population data, since Mendelian inheritance restricts the set of possible solutions. In order to overcome the limitations of classic statistical haplotyping methods, a combinatorial formulation of the HI problem on pedigrees has been proposed in the literature, called Minimum-Recombinant Haplotype Configuration (MRHC) problem, that allows a single type of genetic variation events, namely recombinations. In this work, we define a new problem, called Minimum-Change Haplotype Configuration (MCHC), that extends the MRHC formulation by allowing also a second type of natural variation events: mutations. We propose an efficient and accurate heuristic algorithm for MCHC based on an L-reduction to...

• Type: Journal
• Year: 2010
• Where: WABI
• Authors: Yuri Pirola, Paola Bonizzoni, Tao Jiang
• Keywords: Bioinformatics, WABI 2010